Abstract Paper

Journal of Computing and Intelligent Systems - JCIS

Title	: COMBINED FUZZY AND PROJECTION BASED LEARNING IN META-COGNITIVE NEURAL NETWORK FOR MAMMOGRAM CLASSIFICATION
Author(s)	: S PADMA, R PUGAZENDI
Article Information	: Volume 4 - Issue 1 (May - 2020) , 93 - 98
Affiliation(s)	: Research Scholar, Research and Development Center, Bharathiyar University Coimbatore, India
	: Assistant Professor, Department of Computer Science, Government Arts College, Salem, India

Abstract :

Breast cancer is the life threatening disease nowadays especially for the women. Several methods have been developed in early identification of this disease. The traditional RBF network when combined with fuzzy and projection based learning performs better in benchmark datasets. This concept is combined with the meta cognitive principles. The McNN has two components namely the cognitive component and the meta cognitive component. The cognitive component hold the normal RBF and the meta cognitive the copy of the cognitive component along with learning strategies. In this article the MIAS mammogram dataset is taken and several trials were taken to prove the betterment of the proposed method compared to support vector machine (SVM) and self-regulatory resource allocation network (SRAN).

Keywords	: Mammogram, Meta cognitive neural network
Document Type	: Research Paper
Publication date	: February 01, 2020